Ekaterina Kutafina

This paper develops a hybrid model for spike sorting in C-fiber microneurography, achieving better F1-scores and fewer false positives than Spike2 software.

The paper evaluates supervised spike sorting for noisy single-electrode recordings from human C-nociceptors, finding raw signal features outperform complex methods and recommending tailored approaches.

This paper introduces a computational model to predict conduction velocity changes in unmyelinated axons using memory-based mechanisms, showing improved efficiency compared to Hodgkin-Huxley models.